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A comparative study of safety climate differences in healthcare and the petroleum industry
  1. Espen Olsen,
  2. Karina Aase
  1. University of Stavanger, Stavanger, Norway
  1. Correspondence to Professor Karina Aase, Department of Health Studies, University of Stavanger, Faculty of Social Sciences, Stavanger N-4036, Norway; karina.aase{at}uis.no

Abstract

Aim The aim of this article is to compare safety climate in healthcare and the petroleum industry by collecting empirical evidence of differences between the two sectors.

Methods The Hospital Survey on Patient Safety Culture (HSOPSC) is used to measure the safety climate in two organisations operating in the two different sectors: (1) a large Norwegian university hospital offering a wide range of hospital services and (2) a large Norwegian petroleum company producing oil and gas worldwide.

Results and discussion Statistical analyses supported the expected hypotheses that safety climate is positively related to outcome measures and that the level on safety climate and outcome measures are generally higher in the petroleum sector. Empirical findings indicate that healthcare should learn from the petroleum industry regarding safety improvement efforts, and the implication of this is discussed in the paper.

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Introduction

Safety climate generally has the potential to vary within1 as well as between organisations2 and sectors.3 Safety climate features used in healthcare are most often adapted from other industries. This research trend indicates that cross-industrial overlaps exist with regard to safety-related concepts and challenges. Previous research has suggested that the safety climate level is less ‘ideal’ in hospitals compared with the aviation sector,3 4 but there is a lack of studies assessing safety climate across sectors.

The aim of the present study is to investigate differences in safety climate between employees in healthcare and the petroleum industry. The empirical data used in the study stem from two parallel research projects: one patient safety study of a large Norwegian university hospital and one safety programme study of an international petroleum company with head offices in Norway. Safety climate assessments were conducted as part of both projects, making it possible to conduct comparisons between the two sectors.

Safety climate differences

Even though today the petroleum industry is generally considered to be safe,5 this has not always been the case. Haukelid described the evolution of safety through four stages in the petroleum industry (Haukelid;6 see also Hudson7). The first stage (1966–1980) was characterised by a macho culture with severe accident rates; the second stage (the 1980s) was characterised by a great change through new technology, committed leadership and employee participation; in the third stage (the 1990s) attention was directed towards safety-management systems; while the fourth and subsequent stage (2000–present) has focused on improving safety culture. In Norway, the Petroleum Safety Authority in 2001 implemented a new regulation stating that companies operating on the Norwegian shelf should encourage and promote a sound culture for health, safety and environment. Today, it is common within many companies in the Norwegian petroleum industry to implement safety programmes with the aim of improving safety culture among workers. This is based on a common understanding that human behaviour is crucial in achieving the goal of zero accidents.

The current petroleum company included in this study has additionally invested extensively in safety activities for a long period of time. The overall aim of these activities has been to improve safety behaviour and safety culture by introducing different safety interventions.

Compared with the petroleum industry, healthcare has lacked the same attention towards safety systems and safety culture. Several studies8–11 indicate unacceptable levels of adverse events (2.9–16.6% of patient admissions), and several governmental health agencies have expressed concerns regarding patient safety.12 13 The concerns have been agreed upon by researchers, stating that for instance hospital systems are designed to rely on the error-free performance of individuals.14 If this is the case, the attitude is substantially different from the petroleum industry where human error is considered inevitable, and risks are understood as combinations of active failures and latent conditions.15 Two studies have compared safety climate dimensions in healthcare and aviation. Both studies found the safety climate levels to be lower among healthcare workers than among aviation workers. Sexton et al concluded that medical staff found it hard to discuss errors and that errors were not handled appropriately among hospital workers.4 Gaba et al reported that perceived safety problem areas among hospital workers were up to 12 times the amount perceived by aviation workers within certain areas.3 Based on the above, it would be reasonable to expect that workers in the petroleum industry perceive the safety climate level to be higher than workers within healthcare: employees' perceptions of safety climate are higher among workers within the petroleum industry than among workers within the healthcare sector (Hypothesis 1).

Safety climate outcomes

The safety climate concept was traditionally developed to explain additional variation in safety related outcomes.16 Associations between safety climate and safety performances have been documented both directly and indirectly.

Griffin and Neal illustrated how workers' knowledge, skills and motivation mediated the effect of safety climate on safety performance.17 Later studies have also illustrated the indirect effects of safety climate.18 19 In the theoretical models developed by Zohar1 and Flin,5 they proposed that the effect of safety climate on safety outcomes is mediated through individual workers' motivation and behaviour. In other words; safety motivation and behaviour, as well as lower accidents levels, can be expected outcomes of a good safety climate. The link between safety climate and self-reported safety behaviour has been supported by DeJoy et al, and more recently Johnson demonstrated that safety climate predicted accidents in a manufacturing organisation.20 21 Based on the above, it would be reasonable to expect a positive relation between workers' perception of safety climate and desirable safety outcomes both in healthcare and in the petroleum industry. Since perceived safety climate is expected to be higher within the petroleum industry than within healthcare (Hypothesis 1), it is furthermore reasonable to expect that the perceived level of safety climate outcomes is higher in the petroleum industry than in healthcare: safety climate dimensions positively influence workers' perception of safety outcomes both in petroleum and in healthcare (Hypothesis 2).

Method

Instrument

A review of available safety climate instruments was conducted to investigate the factorial structure and psychometric properties of instruments. The Hospital Survey on Patient Safety Culture (HSOPSC) was selected mainly because the dimensionality covered general topics revealed as important in a broader patient safety study,22 and because studies show that HSOPSC has met more psychometric criteria compared with other instruments.23 The dimensionality of HSOPSC is conventional, measuring several dimensions that are typical within the safety theory of both healthcare and other industries.23 All items in HSOPSC are rated on Likert-type scales with verbal anchors. ‘Number of events reported (last 12 months)’ is measured on a scale from 1 to 6; all other concepts are measured on scales from 1 to 5 (more details on HSOPSC at http://www.ahrq.gov/qual/hospculture).

HSOPSC was validated on hospital data before distribution to the petroleum sample.24 Some limitations of the instruments were revealed: ‘Number of events reported (last 12 months)’ and ‘Frequency of event reporting’ did not function well as outcome variables, and were therefore not included in the study.

The original version of HSOPSC was translated into Norwegian before distribution to the hospital sample.24 Some adaptations of the HSOPSC instrument were conducted before distribution to the petroleum sample. The term ‘patient’ was removed from items in the instrument. For example, the item measuring perceived safety outcome, ‘Give a general judgement about the patient safety in your department’ (Pasient safety grade), was rephrased into ‘Give a general judgement about the safety in your department’ (Safety Grade) in the petroleum sample. As a result of meetings with safety experts in the petroleum company, nine items were removed in order to trim the original version of HSOPSC to increase the workers' understanding of the questionnaire. This resulted in removing the outcome measure ‘Overall perceptions of safety.’ A new outcome measure concerning the likelihood of an employee stopping to work in dangerous situations was added. This measure was already included in the instrument used in the hospital sample. The dimension ‘Stop working in dangerous situations’ consisted of three items (‘I ask my colleagues to stop work, that is, dangerously accomplished,’ ‘I notify if I see dangerous situations’ and ‘I stop working if I consider the situations to be dangerous for me or my colleagues’). Finally, a ‘do not know’ category was added to seven items measuring safety climate at the organisational level and to the ‘Safety grade’ measure.

After adapting the HSOPSC instrument to the petroleum sample, a total of 37 items could be used to analyse cross-sectional differences.

Questionnaire samples

The target group in the hospital included all patient-related employee categories and other personnel employed in the same working environment. A total of 1919 workers answered the survey at the hospital, resulting in a response rate of 55%. Of these respondents, 89% had direct patient contact, whereas 62% worked between 20 and 37 h per week.

For the petroleum company, 1806 workers answered the survey resulting in a response rate of 52%. The sample includes 296 contract workers of four different subcontractors working for the petroleum company. In the petroleum sample, 45% had a job of administrative character, and 44% were employed in jobs offshore.

Printed questionnaires in Norwegian were distributed to the hospital sample. In the petroleum company, HSOPSC was distributed electronically via email in both English and Norwegian. In both samples, the respondents answered anonymously.

Statistical procedures

Data were analysed using SPSS 13.0 (SPSS, Chicago, Illinois). The level of scores in the ‘do not know’ category was low, and was therefore treated as missing values before the remaining analyses were conducted. As explained by Sorra and Nieva, mean scores for the dimensions were created after reversing the coding for reverse items.25 To determine if factor scales yielded acceptable α coefficients and internal consistency, the Cronbach α was estimated. Multiple analysis of variance (MANOVA) was used to test whether or not there was an overall difference in employee perceptions of safety climate and safety outcomes. t Test statistics were estimated to test if the mean differences were significant for each measurement concept. Pearson r and regression analyses were estimated separately for each sector to investigate if the safety climate dimensions were positively correlated with the outcome variables.

Results

Internal consistency

The Cronbach α was estimated for both samples (table 1). The α scores ranged from 0.39 to 0.82 in the petroleum sample, and from 0.38 to 0.78 in the hospital sample. In the petroleum sample, the lowest α score was estimated for the dimension measuring Staffing (0.39), and likewise Teamwork across units (0.38) was the dimension with the lowest score in the hospital sample. In contrast to a high α score, lower scores indicate that the dimension measures a wider domain.26 Since α scores are sensitive to the number of items in the dimensions, this may explain the scores lower than 0.70, since these are estimated based on dimensions measured with only two or three items.27 The aim of this study was to explore the safety climate differences between two sectors. Based on this, no threshold for α scores was defined for the dimensions, and all dimensions are included in the remaining analyses.

Table 1

Internal consistency of measures

Differences between samples

MANOVA and t test statistics were conducted to investigate the differences in safety climate and safety outcomes between workers in healthcare and the petroleum industry. MANOVA revealed that there was an overall difference in the safety climate between the two industries when the 10 dimensions were used as dependent variables, and sector was defined as a dichotomised (hospital vs petroleum) independent variable: Wilks λ of 0.624 (df=10), p<0.001, effect size=0.376 (η2). Hence, the results therefore generally support the hypothesis that safety climate differs across the hospital and petroleum sample. MANOVA, using the same dichotomised independent variable, also revealed an overall difference in the two outcome variables used in the study: Wilks λ of 0.920 (df=2), p<0.001, effect size=0.080 (η2).

Mean differences and t tests are shown in table 2. These analyses provide additional information to MANOVA because the t tests estimate whether differences between sectors are significant for each measurement concept.

Table 2

Descriptive statistics and mean differences between the sectors

The t-test analyses indicate that safety climate is higher in the petroleum industry, with the exception of two dimensions: the difference regarding ‘Communication openness’ was not significant and contrary to what was expected, ‘Non-punitive response to error’ has a higher score in the hospital sample. The difference between the mean scores is highest for the dimension ‘Organisational management support for (patient) safety’ (0.98), followed by ‘Teamwork across units’ (0.43) and ‘Feedback and communication about errors’ (0.43).

It was also estimated whether workers in the petroleum industry scored higher than workers in healthcare on two measures used for measuring the safety level in general: ‘Frequency of no harm reporting’ and ‘Number of events reported.’ On both measures, t test statistics revealed higher scores in the petroleum industry than in healthcare.

Associations with outcome measures

Regression analyses (table 3) and Pearson r were estimated to investigate the association between the safety climate dimensions and outcome measures. All correlations between the safety climate dimensions and the two outcome measures were positively correlated (p<0.001, two-tailed), both in the total sample and when the analyses were conducted separately for the two sectors. In the hospital sample, the safety climate dimensions were correlated between 0.11 and 0.32 with ‘Stop working in dangerous situations,’ and between 0.22 and 0.45 with ‘Patient safety grade.’ In the petroleum sample, the safety climate correlations with ‘Stop working in dangerous situations’ varied between 0.17 and 0.45 and similarly between 0.17 and 0.37 with the ‘Safety grade’ dimension.

Table 3

Regression analyses with standardised β coefficients

In the regression analyses, the ‘(Patient) safety grade’ and ‘Stop working in dangerous situations’ were defined as dependent variables, and the safety climate dimensions as independent variables. In the estimations, analyses were separated for the two sectors. Except for one negative influence from ‘Non-punitive response to error,’ regression analyses generally support the hypothesis that safety climate dimensions have positive influences on workers perception of safety outcome variables. The most consistent influences are in the hospital sample where six out of 10 safety climate dimensions have positive influences on ‘Patient safety grade,’ while five positive influences were revealed in the petroleum sample on ‘Safety grade.’ The safety climate dimensions are also generally positively related to ‘Stop working in dangerous situations’; five significant positive relations in the hospital sample, and six significant positive relations in the petroleum sample.

Discussion

Generally, results support the usability of HSOPSC in the petroleum sample after minor adjustments of the instrument. With some exceptions, the Cronbach α scores are satisfactory considering the low number of items for some of the measures. Some precautions, however, should be made regarding comparing dimensions with low α scores. Correlations in both samples show a moderate association among the safety climate dimensions, indicating a discriminant validity of measures.

As expected, results using MANOVA indicate an overall difference in the level of safety climate and safety outcomes between the two sectors. t Test statistics indicate a higher level on all measures among petroleum workers (hypothesis 1), with the exceptions of ‘Communication openness’ and ‘Non-punitive response to errors.’ Generally, a low degree of missing responses was not a problem in the study. Also, both samples are believed to be representative for the target samples in the study. In sum, the empirical data and statistical results show that data from the two samples can be compared. With one significant exception, ‘Non-punitive response to errors,’ all the significant β coefficients and all correlations are positively associated with the outcome measures. This demonstrates that the safety climate dimensions influence the outcome variables to a high degree as expected (Hypothesis 2).

The study has shown that safety climate can be measured using the same validated instrument (HSOPSC) across work domains. So far, only a few studies have attempted to do so,3 4 even though the need for research to understand risk issues across sectors has been raised.28 29 At the same time, certain limitations of the study should be mentioned. First, only one hospital represents the healthcare sector, while several companies represent the petroleum sector. Research has shown that the safety climate may vary between organisations,2 and so the samples in this study may not represent the two sectors in general. Second, minor adjustments were conducted to make HSOPSC suitable for the petroleum sample. Caution therefore should be exercised when directly comparing the two sectors. Third, the outcome measures used in the study are measured with the same questionnaire as the safety climate dimensions, limiting the criterion validity of the study. Finally, many reasons for why ‘Non-punitive response to errors’ has a higher score in healthcare than in the petroleum industry can be offered. One explanation might be that a low safety focus in general influences hospital workers' perception of not feeling blamed. The inverse relation estimated with regression analyses between ‘Non-punitive response to errors’ and ‘Stop working in dangerous situations’ in the hospital sample gives an additional indication that caution should be exercised in analysing the higher score in healthcare on this dimension. Caution also should be taken when interpreting dimensions with low scores on Cronbach α.

Our results have shown that the level of safety climate in the hospital setting is less advanced than the petroleum industry. The most substantial difference between the two sectors is measured on the dimension ‘Organisational management support for (patient) safety.’ Thus, top-level healthcare managers could learn from petroleum managers how to put patient safety on the organisational agenda. Other findings at the organisational level document that the healthcare sector could improve their capabilities on the dimensions ‘Teamwork across units’ and ‘Organisational handoffs and transitions.’ As a consequence, healthcare providers should consider introducing improvement efforts at an overall organisational and strategic level in addition to tactical and practical issues at the department level, where department managers have a particular role in the patient-safety improvement measures. Our results suggest that healthcare could improve further on the following dimensions: ‘Supervisor/manager expectations and actions promoting safety,’ ‘Feedback and communication about error,’ ‘Organisational learning—continuous improvement’ and ‘Teamwork within units.’ Finally, compared with petroleum, healthcare could improve the alignment between work tasks and human resources. In addition to increasing patient safety, this could potentially decrease stress and increase the general health status of healthcare workers. Healthcare workers have better scores on ‘Non-punitive response to error’ than petroleum workers. Effort should be made to uphold this level when safety improvements are introduced to improve the other safety climate dimensions.

Even though the contextual settings and the types of risks are highly different between hospitals and petroleum companies, it is appropriate to suggest how the safety management systems in the petroleum setting might possibly benefit healthcare. It is important to note that the petroleum industry has a strong regulatory regime that specifies very clearly the safety and risk issues that should be addressed in the petroleum companies. These regulatory requirements have influenced the petroleum industry to take actions at different levels. An example is the role of safety delegates in the petroleum industry of having a substantial impact on work processes and giving direct input to managers. Also included in the regulatory regime is the inclusion of a safety culture formalisation in the Norwegian Petroleum Safety Authority's (PSA) regulations which stresses the systematic development of a sound health, environment, and safety culture in all petroleum activities (PSA 2002, The Framework Regulations, Section 11). As indicated, this specific demand in the regulatory framework has influenced petroleum companies to take specific actions in order to address cultural issues relating to health, environment and safety.28 One example is the implementation of comprehensive safety programmes and campaigns. In the petroleum company included in this study, the safety programme involved 33 000 workers with a 3-year implementation plan incorporating five specific strategies that focused on: (1) correct prioritisation (taking the time needed to work safely, ie, safety is more important than production), (2) compliance (emphasises the importance of following procedures, requirements, guidelines and decisions), (3) open dialogue (enables employees to feel free to discuss safety issues with colleagues and managers at any level, (4) continuous risk assessment (taking the time to evaluate potential incidents and accidents related to unexpected activities) and (5) caring about colleagues (taking care of others and oneself when doing something that puts individuals at risk).30

The safety-management systems for preventing risk and improving safety performance in the Norwegian petroleum industry were developed over several decades. It is recognised that a focus on patient safety is relatively new in healthcare. Hence, we are encouraged by the opportunities, where appropriate, that exist for healthcare organisations to learn and to develop truly pervasive safety cultures based on the highly formalised programmes briefly described here.

Acknowledgments

The authors would like to thank the employees in the two sectors for participating in the survey.

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Footnotes

  • Funding The study is partly funded by the Norwegian Research Council, the participating hospital, and the petroleum company. The funding sources have had no role in the development of this paper.

  • Competing interests None.

  • Provenance and peer review Not commissioned; externally peer reviewed.

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